Conference item
Predicting the growth of morphological families from social and linguistic factors
- Abstract:
- We present the first study that examines the evolution of morphological families, i.e., sets of morphologically related words such as “trump”, antitrumpism”, and “detrumpify”, in social media. We introduce the novel task of Morphological Family Expansion Prediction (MFEP) as predicting the increase in the size of a morphological family. We create a ten-year Reddit corpus as a benchmark for MFEP and evaluate a number of baselines on this benchmark. Our experiments demonstrate very good performance on MFEP.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Accepted manuscript, 1.9MB)
-
- Publisher copy:
- 10.18653/v1/2020.acl-main.649
Why is the content I wish to access not available via ORA?
Bibliographic data (the information relating to research outputs) and full-text items (e.g. articles, theses, reports, etc.) arrive in ORA from several different sources. Unfortunately we are not able to make available the full-text for every research output.
Please contact the ORA team (
) if you have queries regarding unavailable content OR if you are aware of a full-text copy we can make available.
) if you have queries regarding unavailable content OR if you are aware of a full-text copy we can make available.
Content may be unavailable for the following four reasons
-
Version unsuitable
-
We have not obtained a suitable full-text for a given research output. See this page for more information.
-
Recently completed
-
Sometimes content is held in ORA but is unavailable for a fixed period of time to comply with the policies and wishes of rights holders.
-
Permissions
-
All content made available in ORA should comply with relevant rights, such as copyright. See this page for more information.
-
Clearance
-
Some thesis volumes scanned as part of the digitisation scheme funded by Dr Leonard Polonsky are currently unavailable due to sensitive material or uncleared third-party copyright content. We are attempting to contact authors whose theses are affected.
Alternative access to the full-text
You may be able to access the full-text directly from the publisher's website using the 'Publisher Copy' link in the 'Links & Downloads' box from a research output's ORA record page. This method may require an institutional or individual subscription to the journal/resource.
Authors
Bibliographic Details
- Publisher:
- ACL Publisher's website
- Journal:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics Journal website
- Issue:
- 2020
- Pages:
- 7273–7283
- Host title:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Publication date:
- 2020-07-29
- Acceptance date:
- 2020-04-04
- Event title:
- 2020 Annual Conference of the Association for Computational Linguistics
- Event location:
- Hyatt Regency Seattle Hotel
- Event website:
- https://acl2020.org/
- Event start date:
- 2020-07-05T00:00:00Z
- Event end date:
- 2020-07-10T00:00:00Z
- DOI:
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1102690
- Local pid:
- pubs:1102690
- Deposit date:
- 2020-05-03
Terms of use
- Copyright holder:
- Association for Computational Linguistics
- Copyright date:
- 2020
- Rights statement:
- © 2020 Association for Computational Linguistics.
- Notes:
- This is the accepted manuscript version of the article. The publisher's version is available from ACL at: http://dx.doi.org/10.18653/v1/2020.acl-main.649
If you are the owner of this record, you can report an update to it here: Report update to this record